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Title:

Agent-Based Model of Electric Vehicle Charging Demand for Long-Distance Driving in the State of Indiana

Accession Number:

01852628

Record Type:

Component

Availability:

Find a library where document is available


Order URL: http://worldcat.org/issn/03611981

Abstract:

Historically the U.S. transportation system has been continuously improved to adopt new policies and technologies. The transportation vehicle energy transition from fossil fuels to electricity is promoted by policymakers and major automakers with an expectation of enhancing sustainability aspects such as fossil fuel consumption reduction, carbon emissions reduction, and lower operations and maintenance costs. However, the electrification of the existing transportation infrastructure system requires substantial upgrades to overcome two major concerns from ordinary drivers and the public. One is the driver’s range anxiety based on the current capability of the electric vehicle (EV) technologies. The other is the availability of EV charging stations near the planned route. To address these two issues, we introduce an agent-based simulation model to project the consequences of electrification in the Indiana state highway system. Specifically, the model is developed to monitor the status of long-distance EV trips between different regions. The multi-agent engine method guarantees the model can adapt to diverse scenarios and complex environments. The simulation experiment verifies that the proposed model can provide the expected outcomes, including the numerical data of electric energy demand and the geospatial information (as location coordinates) of failed trips. By performing a GIS-based analysis of the results, the derived geospatial data can help state transportation agencies determine where to deploy the charging facilities to satisfy the overall charging demand. The proposed simulation framework offers a novel and strategic way to resolve the challenges for EV charging-related research and projects.

Supplemental Notes:

Kyubyung Kang https://orcid.org/0000-0001-7293-2171© National Academy of Sciences: Transportation Research Board 2022.

Report/Paper Numbers:

TRBAM-22-02332

Language:

English

Authors:

Chen, Donghui
Kang, Kyubyung

ORCID 0000-0001-7293-2171

Koo, Dan Daehyun

ORCID 0000-0001-8577-7692

Peng, Cheng
Gkritza, Konstantina

ORCID 0000-0002-6598-4771

Labi, Samuel

ORCID 0000-0001-9830-2071

Pagination:

pp 555-563

Publication Date:

2023-2

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Volume: 2677
Issue Number: 2
Publisher: Sage Publications, Incorporated
ISSN: 0361-1981
EISSN: 2169-4052
Serial URL: http://journals.sagepub.com/home/trr

Media Type:

Digital/other

Features:

Figures; References (20) ; Tables

Geographic Terms:

Indiana

Subject Areas:

Energy; Highways; Operations and Traffic Management; Planning and Forecasting; Terminals and Facilities; Vehicles and Equipment

Files:

TRIS, TRB, ATRI

Created Date:

Jul 19 2022 12:23PM